Branching Songs
Bibliographic record
Abstract
In cities, trees are seen predominantly as entities that beautify streets, parks and gardens. Often they’re regarded as obstacles to urban development, where their importance to ecosystem health plays a secondary role to economic growth. How can multispecies art offer new perspectives on trees and their crucial contributions to urban life? Branching Songs is a project with old trees in the Vancouver area, including the ‘1308 Trees’, urban forest sites where trees are being cleared for the Transmountain Pipeline expansion. The intention is to bear witness to trees who are supporting the well-being of human and nonhuman life. The project combines new technologies, such as 360° photography and video, ambisonic and geophonic sound recording, biomidi data, and contact mic recording, with approaches from acoustic ecology, multispecies creativity, and performance. The Branching Songs team produced methods for working collaboratively with trees and composed a collection of soundscapes and accompanying 360° photos and videos. The soundscapes present the complex biophony and anthropophony of each site, weaving in soundings from electromagnetic fields produced by the trees and our touch interactions with the tree bodies. The touch gestures are improvisational, responding to the emergent sounds heard on site, and the specific features of the participating tree. Multiple microphones allow us to listen to varied perspectives refracted across the tree body. Our video article includes an introduction to the project, the methods we developed, two soundscape compositions and accompanying visuals with the trees in the collaboration.@font-face{font-family:"Cambria Math";panose-1:2 4 5 3 5 4 6 3 2 4;mso-font-charset:0;mso-generic-font-family:roman;mso-font-pitch:variable;mso-font-signature:-536870145 1107305727 0 0 415 0;}@font-face{font-family:"Helvetica Neue";panose-1:2 0 5 3 0 0 0 2 0 4;mso-font-charset:0;mso-generic-font-family:auto;mso-font-pitch:variable;mso-font-signature:-452984065 1342208475 16 0 1 0;}p.MsoNormal, li.MsoNormal, div.MsoNormal{mso-style-unhide:no;mso-style-qformat:yes;mso-style-parent:"";margin:0in;mso-pagination:widow-orphan;font-size:12.0pt;font-family:"Times New Roman",serif;mso-fareast-font-family:"Times New Roman";}.MsoChpDefault{mso-style-type:export-only;mso-default-props:yes;font-family:"Calibri",sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:Calibri;mso-fareast-theme-font:minor-latin;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:"Times New Roman";mso-bidi-theme-font:minor-bidi;}div.WordSection1{page:WordSection1;}
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.184 | 0.060 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".